At present, facing massive financial data, it is impossible to effectively classify the characteristics of financial data, and there is a problem of low accuracy of financial early warning. Therefore, this paper proposed a financial early warning system based on the improved C4.5 algorithm. First, the traditional C4.5 algorithm is used to preprocess the original financial data to reduce the redundancy of data attributes. On this basis, C4.5 algorithm is improved by integrating with Shannon’s Information theory, transforming attributes with performance patterns into interval values, classifying different financial status data, constructing decision trees, and designing a financial early warning system. Experimental simulations have shown that the designed financial early warning system has high practical value.